In this paper we present a method to optimize the overhead in dynamically reconfigurable computing systems. Applications are considered to be partitioned into algorithmic blocks. Our method allows a reduction of overhead when reconfiguration between those blocks is required. For each block a variety of specifications is constructed using high level algorithmic transformations based on a partitioning method for nested loop programs. The partitioning method allows an efficient verification with the given design constraints. The specifications differ in resource usage and execution time. The reconfiguration costs are reduced by finding the best matching specifications of the algorithmic blocks. The specifications with the lowest reconfiguration cost are selected for implementation using the matching information as input for the implementation tools. Finally we present an optimal solution for a reconfigurable 2D mean filter. Two configurations with different filter sizes and word widths were implemented according to the matching specifications. We reduced the required logic area compared to the non-reconfigurable implementation and reduced significantly the reconfiguration costs.